“Image-based Rendering from a Sparse Set of Images” by Zickler, Enrique, Ramamoorthi and Belhumeur
Conference:
Type(s):
Title:
- Image-based Rendering from a Sparse Set of Images
Session/Category Title: Image-Based Rendering
Presenter(s)/Author(s):
Abstract:
When the shape of an object is known, its appearance is deter- mined by the spatially-varying bi-directional reflectance distribution function (SBRDF) defined on its surface. We present a method for recovering the SBRDF of a surface with known geometry from a sparse set of images. Unlike existing parametric methods (e.g., [Sato et al. 1997]) this approach does not require a choice of an analytic BRDF model, and is therefore capable of capturing arbitrary, complex reflectance effects. It is also different from existing non-parametric methods (e.g. [Matusik et al. 2002]) that are purely data-driven and can require thousands of images; unlike these methods, we exploit spatial coherence, which can drastically reduce the number of required input images.
References:
Matusik, W., Pfister, H., Brand, M., and McMillan, L. 2002. Image-based 3D photography using opacity hulls. ACM Transactions on Graphics (Proc. ACM SIGGRAPH) 21, 3, 427–437.
Matusik, W., Pfister, H., Brand, M., and McMillan, L. 2003. A data-driven reflectance model. ACM Transactions on Graphics (Proc. ACM SIGGRAPH) 22, 3, 759–769.
Sato, Y., Wheeler, M. D., and Ikeuchi, K. 1997. Object shape and reflectance modeling from observation. In Proceedings of ACM SIGGRAPH, 379–387.
